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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 7451–7475 of 9051 papers

TitleStatusHype
Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution—0
Policy Manifold Search for Improving Diversity-based Neuroevolution—0
Policy Space Diversity for Non-Transitive Games—0
Political representation bias in DBpedia and Wikidata as a challenge for downstream processing—0
Political Strategies to Overcome Climate Policy Obstructionism—0
POLYGLOT-NER: Massive Multilingual Named Entity Recognition—0
Polyhedral Conic Classifier for CTR Prediction—0
PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts—0
Polymorphism in rapidly-changing cyclic environment—0
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization—0
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)—0
Popular News Always Compete for the User's Attention! POPK: Mitigating Popularity Bias via a Temporal-Counterfactual—0
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification—0
Regularized Evolutionary Population-Based Training—0
Population Diversity Leads to Short Running Times of Lexicase Selection—0
Population genetics in microchannels—0
Population size predicts lexical diversity, but so does the mean sea level - why it is important to correctly account for the structure of temporal data—0
Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz—0
PortraitBooth: A Versatile Portrait Model for Fast Identity-preserved Personalization—0
Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification—0
Pose Estimation from Camera Images for Underwater Inspection—0
PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learning—0
Position: Measure Dataset Diversity, Don't Just Claim It—0
Position of Uncertainty: A Cross-Linguistic Study of Positional Bias in Large Language Models—0
Position Paper: Building Trust in Synthetic Data for Clinical AI—0
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